1. Interactive C-cycle in Earth System models
Helge Drange

2. Mean change vs uncertainty
Most of the effort
IPCC (2007)

3. Mean change vs uncertainty
Most of the impact
Most of the effort
Goal:
Improve knowledge and by that better quantify
and, over time,
reduce uncertainty
IPCC (2007)

4. Ex: Long lived GHG warming vs aerosol cooling
IPCC (2007)

5. Ex: Long lived GHG warming vs aerosol cooling
IPCC (2007)

6. Ex: Long lived GHG warming vs aerosol cooling
IPCC (2007)

7. Ex: Long lived GHG warming vs aerosol cooling
How and what if?
Uncertainty about magnitude (not sign) of radiative forcing
IPCC (2007)

8. Size and stability of Earth’s carbon reservoirs
Reference numbers (ca)
(i) Human induced emissions of CO2 per year:
10 Gt-C
(ii) Human generated emissions of carbon, :
300 Gt-C
(iii) Fossil reserves:
5000 Gt-C

9. Uncomfortable zone 10 100 Gt-C 1000 Very likely Likely Unlikely
Highly unlikely 10
100 Gt-C
1000
Gruber et al. (2004)

10. Wetlands and peatlands
Soil carbon
Very
likely
Terrestrial biomass
Likely
Wetlands and peatlands
Unlikely
Permafrost
Highly unlikely 10
100 Gt-C
1000
Gruber et al. (2004)

11. Wetlands and peatlands
Soil carbon
Very
likely
Terrestrial biomass
Likely
Wetlands and peatlands
Unlikely
Permafrost
Highly unlikely
Stability being discussed 10
100 Gt-C
1000
Gruber et al. (2004)

12. Ocean 10 100 Gt-C 1000 Solubility pump Very likely Soft tissue pump
Carbonate pump
Likely
Unlikely
Methane hydrates
Highly unlikely 10
100 Gt-C
1000
Gruber et al. (2004)

13. Ocean 10 100 Gt-C 1000 Solubility pump Very likely Soft tissue pump
Carbonate pump
Likely
Unlikely
Methane hydrates
Highly unlikely
Lack of knowledge 10
100 Gt-C
1000
Gruber et al. (2004)

14. Size and stability of Earth’s carbon reservoirs
Summary:
Large reservoirs of carbon are found on land and in the ocean. These reservoirs have the potential to greatly influence Earths climate
(pending on time scale and degree/speed of warming)

15. Climate projections Traditional approach
Off-line scenarios from population, energy, economics models
EMISSIONS
CONCENTRATIONS
CO2, methane, etc.
Off-line carbon cycle and chemistry models
Coupled climate models
HEATING EFFECT
‘Climate Forcing’
CLIMATE CHANGE
Temp, rain, sea-level, etc.
How do we go about estimating climate change in the future? This is done in a number of stages, shown in this figure. The first thing we need to know is what the emissions will be of greenhouse gases and other gases which affect climate change. These projections are deduced from separate models which take into account population growth, energy use, economics, technological developments, and so forth. We do not carry out this stage at the Hadley Centre, but we take future scenarios of these emissions from others, particularly IPCC.
Having obtained projections of how emissions will change, we then calculate how much remains in the atmosphere, ie what future concentrations will be. For CO2, this is done using a model of the carbon cycle, which simulates the transfer of carbon between sources (emissions) and sinks in the atmosphere, ocean and land (vegetation). For gases such as methane, we use models which simulate chemical reactions in the atmosphere.
Next we have to calculate the heating effect of the increased concentrations of greenhouse gases; this is often called climate forcing. This is done within the climate model, described shortly, which generates spatial patterns of changes in temperature, rainfall and sea level etc., across the surface of the earth and through the depth of the atmosphere and oceans.
Following on from the climate change prediction, the impacts of climate change, on socio-economic sectors such as as water resources, food supply, flooding, are calculated by other research groups. Hadley Centre model predictions are made freely available to the impacts community and well over 100 groups have now used the data.
IMPACTS
Flooding, food supply, etc.
Off-line impacts models

16. Climate projections Biogeochemical feedbacks included
Off-line scenarios from population, energy, economics models
EMISSIONS
CONCENTRATIONS
CO2, methane, etc.
Off-line carbon cycle and chemistry models
Coupled climate models
HEATING EFFECT
‘Climate Forcing’
CLIMATE CHANGE
Temp, rain, sea-level, etc.
How do we go about estimating climate change in the future? This is done in a number of stages, shown in this figure. The first thing we need to know is what the emissions will be of greenhouse gases and other gases which affect climate change. These projections are deduced from separate models which take into account population growth, energy use, economics, technological developments, and so forth. We do not carry out this stage at the Hadley Centre, but we take future scenarios of these emissions from others, particularly IPCC.
Having obtained projections of how emissions will change, we then calculate how much remains in the atmosphere, ie what future concentrations will be. For CO2, this is done using a model of the carbon cycle, which simulates the transfer of carbon between sources (emissions) and sinks in the atmosphere, ocean and land (vegetation). For gases such as methane, we use models which simulate chemical reactions in the atmosphere.
Next we have to calculate the heating effect of the increased concentrations of greenhouse gases; this is often called climate forcing. This is done within the climate model, described shortly, which generates spatial patterns of changes in temperature, rainfall and sea level etc., across the surface of the earth and through the depth of the atmosphere and oceans.
Following on from the climate change prediction, the impacts of climate change, on socio-economic sectors such as as water resources, food supply, flooding, are calculated by other research groups. Hadley Centre model predictions are made freely available to the impacts community and well over 100 groups have now used the data.
IMPACTS
Flooding, food supply, etc.
Off-line impacts models

17. Climate projections Earth System Model
Off-line scenarios from population, energy, economics models
EMISSIONS
Earth System Model
HEATING EFFECT
‘Climate Forcing’
CLIMATE CHANGE
Temp, rain, sea-level, etc.
CONCENTRATIONS
CO2, methane, etc.
(future ?)
Standard for
the IPCC AR5
(due 2013/14)
How do we go about estimating climate change in the future? This is done in a number of stages, shown in this figure. The first thing we need to know is what the emissions will be of greenhouse gases and other gases which affect climate change. These projections are deduced from separate models which take into account population growth, energy use, economics, technological developments, and so forth. We do not carry out this stage at the Hadley Centre, but we take future scenarios of these emissions from others, particularly IPCC.
Having obtained projections of how emissions will change, we then calculate how much remains in the atmosphere, ie what future concentrations will be. For CO2, this is done using a model of the carbon cycle, which simulates the transfer of carbon between sources (emissions) and sinks in the atmosphere, ocean and land (vegetation). For gases such as methane, we use models which simulate chemical reactions in the atmosphere.
Next we have to calculate the heating effect of the increased concentrations of greenhouse gases; this is often called climate forcing. This is done within the climate model, described shortly, which generates spatial patterns of changes in temperature, rainfall and sea level etc., across the surface of the earth and through the depth of the atmosphere and oceans.
Following on from the climate change prediction, the impacts of climate change, on socio-economic sectors such as as water resources, food supply, flooding, are calculated by other research groups. Hadley Centre model predictions are made freely available to the impacts community and well over 100 groups have now used the data.
IMPACTS
Flooding, food supply, etc.
Off-line impacts models

18. Land processes

19. Biogeochemical processes on land
Arneth et al., Nature Geosci. (2010)

20. Biogeochemical processes on land
Arneth et al., Nature Geosci. (2010)

21. Biogeochemical processes on land
Arneth et al., Nature Geosci. (2010)

22. Biogeochemical processes on land
Tropospheric O3  NPP
Arneth et al., Nature Geosci. (2010)

23. Biogeochemical processes on land
Soil NOx +BVOC  O3 formation & CH4 lifetime
Arneth et al., Nature Geosci. (2010)

24. Key challenge: To identify and understand zero-order processes
Biogeochemical processes on land
Similar for the ocean.
Key challenge: To identify and understand zero-order processes
(on the spatial and temporal
scale of interest)
BVOC  Biogenic secondary aerosols
Arneth et al., Nature Geosci. (2010)

25. Early findings

26. Enhanced warming with interactive carbon cycle?
w/interactive CO2
Standard SRES A2 (IPCC AR4)
Friedlingstein et al. (2006)

27. Enhanced warming with interactive carbon cycle?
w/interactive CO2
Standard SRES A2 (IPCC AR4)
Tendency for more CO2 remaining in the atmosphere, and for additional warming
w/interactive CO2
Standard SRES A2 (IPCC AR4)
Friedlingstein et al. (2006)

28. CO2 flux from ocean to atmosphere (from EU project ENSEMBLES)6
Hadley INGV
IPSL Bjerknes
MPI Model mean 4 2
Gt-C / yr -2 -4 -6
Johns et al., Clim. Dynamics (2011)

29. CO2 flux from ocean to atmosphere (from EU project ENSEMBLES)6
Reduced ocean uptake of CO2 is mainly caused by increased temperature in the ocean surface waters
 Reduced CO2 solubility
 Enhanced stratification and reduced vertical mixing
Partly also reduced
biological production
Hadley INGV
IPSL BCCR
MPI Model mean 4 2
Gt-C / yr -2 -4 -6
Johns et al., Clim. Dynamics (2011)

30. CO2 flux from land to atmosphere (from EU project ENSEMBLES)6
Hadley INGV
IPSL Bjerknes
MPI Model mean 4 2
Gt-C / yr -2 -4 -6
Johns et al., Clim. Dynamics (2011)

31. Two degrees target

32. Permissible emissions with interactive CO2
SP550
SP1000
Stabilization at SP550 requires a cumulative 24% reduction of permissible emissions due to positive carbon cycle feedback (23% for SP1000)
MIROC integrated Earth System Model (Kawamiya et al.)

33. Ocean acidification (and timescales involved)
Ω (saturation state of calcite)
Ilyina & Zeebe (2012)

34. Short-term confusion & long-term gain
(or academic learning phase vs practical applicability)

35. Communication challenge!
Increased complexity will, generally, lead to
(an apparent) growth in model uncertainty,
but overall improvement over time
Simulated
quantity
Communication challenge!
2012
AOGCM  ESM
Uncertainty
Observed (true) value
Time

36. A few practical and pragmatical marks
Projections, commitments, long-term changes and irreversibility…
calls for ESMs
Model verification
Common experience that dynamic biogeochemisty in AOGCMs uncover weaknesses in the model's physics, dynamics and/or numerics
Model evaluation
Availability of relevant observations in stead of lot's of “tuning” parameters
Interdisciplinarity
Math/phys based sciences + biology/chemistry/geology/social sci’s
Model compexity vs
Model resolution, long integrations, ensemble integrations
Model diversity
Few very complex and interacting models vs many simplified models
Model spin-up
Physical vs biogeochemical model ✔
obs !